US2024385269A1PendingUtilityA1
T1rho DISPERSION CHARACTERIZATION BY MAGNETIC RESONANCE FINGERPRINTING
Est. expiryMay 19, 2043(~16.8 yrs left)· nominal 20-yr term from priority
G01R 33/5608A61B 5/004G01R 33/561G01R 33/50
52
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Claims
Abstract
Magnetic resonance fingerprinting (MRF) is used to quantify T1ρ dispersion across spin-lock frequencies and enables simultaneous mapping of T1, T2, and T1ρ dispersion. T1ρ at a specific FSL may be determined by retrospectively computation based on the results of the T1ρ dispersion MRF dictionary and pattern matching results. The T1ρ dispersion characteristic may be used to identify and track tissue parameters (such as osteoarthritis and muscle degeneration) before being expressed in other measurable manners.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A magnetic resonance fingerprinting (MRF) method, comprising:
applying an MRF pulse sequence to tissue of a subject; acquiring magnetic resonance (MR) signal data as a result of the application of the MRF pulse sequence; comparing the MR signal data to a predefined MRF dictionary, the MRF dictionary comprising a model of T 1ρ dispersion; and determining a property of the tissue from the T 1ρ dispersion model based on a result of the comparison.
2 . The method according to claim 1 , wherein T 1ρ dispersion is modeled according to:
T
1
ρ
(
ω
)
=
(
q
2
D
)
2
+
ω
2
γ
2
g
2
D
=
m
2
(
q
2
D
)
2
+
m
2
ω
2
where
T
1
ρ
(
0
)
=
m
2
(
q
2
D
)
2
=
T
2
and
T
1
ρ
(
ω
)
=
T
2
+
(
m
ω
)
2
where γ is a hydrogen gyromagnetic ratio, D is a self-diffusion coefficient, q is a spatial frequency of a local magnetic field variation, g is a mean local magnetic gradient strength, ω is frequency, and m is a mediation coefficient that mediates a strength of a T 1ρ dispersion effect and represents a combination of y, D, and g.
3 . The method according to claim 1 , wherein T 1ρ dispersion is modeled according to:
T
1
ρ
(
ω
)
=
T
2
+
m
ω
where ω is frequency, and m is a mediation coefficient that mediates a strength of a T 1ρ dispersion effect and represents a combination of a hydrogen gyromagnetic ratio, a self-diffusion coefficient, and a mean local magnetic gradient strength.
4 . The method according to claim 1 , wherein the determined tissue property relates to tissue degeneration.
5 . The method according to claim 1 , further comprising:
identifying an osteoarthritis or muscle degeneration condition in the subject based on the identified property.
6 . The method of claim 1 , further comprising:
applying a plurality MRF pulse sequencies; and tracking a change in T 1ρ dispersion of the tissue of the subject over the plurality of applied MRF sequences.
7 . The method of claim 1 , further comprising:
applying a plurality MRF pulse sequencies; and tracking a change in the determined tissue property over the plurality of applied MRF sequences.
8 . The method according to claim 1 , wherein the MRF pulse sequence includes a single fixed spin-lock frequency.
9 . The method according to claim 8 , further comprising:
determining a T 1ρ dispersion by retrospectively determining T 1ρ at a plurality of spin-lock frequencies based on the model of the MRF dictionary.
10 . The method according to claim 1 , wherein the MRF dictionary comprises fingerprints of at least T 1 , T 2 , and m.
11 . The method according to claim 1 , wherein the MR signal data is compared to the predefined MRF dictionary with a machine learning system trained to identify MR properties of the MRF dictionary based on input MR signal data.Join the waitlist — get patent alerts
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